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I am a 𝗣𝗵𝗗 𝗔𝗽𝗽𝗹𝗶𝗲𝗱 𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝗶𝗮𝗻 and 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗖𝗼𝗻𝘀𝘂𝗹𝘁𝗮𝗻𝘁 specializing in 𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝗮𝗹 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴, 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝗳𝗶𝗰 𝗖𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴, 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗠𝗮𝗻𝘂𝘀𝗰𝗿𝗶𝗽𝘁 𝗥𝗲𝘃𝗶𝗲𝘄, 𝗡𝘂𝗺𝗲𝗿𝗶𝗰𝗮𝗹 𝗠𝗲𝘁𝗵𝗼𝗱𝘀, and 𝗧𝗵𝗲𝗼𝗿𝗲𝘁𝗶𝗰𝗮𝗹 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁. 𝗜 𝗵𝗲𝗹𝗽 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵𝗲𝗿𝘀, 𝘂𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝗶𝗲𝘀, 𝗮𝗻𝗱 𝗥&𝗗 𝘁𝗲𝗮𝗺𝘀 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝘀𝗰𝗶𝗲𝗻𝘁𝗶𝗳𝗶𝗰 𝗶𝗱𝗲𝗮𝘀 𝗶𝗻𝘁𝗼 𝗺𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝗮𝗹𝗹𝘆 𝗿𝗶𝗴𝗼𝗿𝗼𝘂𝘀 𝗺𝗼𝗱𝗲𝗹𝘀, 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗲𝗱 𝗰𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗺𝗲𝘁𝗵𝗼𝗱𝘀, 𝗮𝗻𝗱 𝗽𝘂𝗯𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵. Since 2012, I have completed 𝗠𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝟭𝟵𝟬 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝗼𝗻 𝗨𝗽𝘄𝗼𝗿𝗸, helping researchers, engineers, independent scholars, universities, startups, and R&D teams solve complex mathematical and computational problems involving 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁𝗶𝗮𝗹 𝗘𝗾𝘂𝗮𝘁𝗶𝗼𝗻𝘀, 𝗧𝗵𝗲𝗿𝗺𝗼𝗱𝘆𝗻𝗮𝗺𝗶𝗰 𝗦𝘆𝘀𝘁𝗲𝗺𝘀, 𝗖𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴, 𝗡𝘂𝗺𝗲𝗿𝗶𝗰𝗮𝗹 𝗦𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻𝘀, 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝗳𝗶𝗰 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴, 𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝗮𝗹 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻, and 𝗣𝘂𝗯𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻-𝗥𝗲𝗮𝗱𝘆 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗦𝘂𝗽𝗽𝗼𝗿𝘁. Recent engagements have included 𝗺𝘂𝗹𝘁𝗶-𝗽𝗵𝗮𝘀𝗲 𝘁𝗵𝗲𝗼𝗿𝗲𝘁𝗶𝗰𝗮𝗹 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝗿𝗲𝘃𝗶𝗲𝘄𝘀, 𝗵𝗶𝗴𝗵-𝗶𝗺𝗽𝗮𝗰𝘁 𝗷𝗼𝘂𝗿𝗻𝗮𝗹 𝗺𝗮𝗻𝘂𝘀𝗰𝗿𝗶𝗽𝘁 𝗽𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻, referee-level 𝗺𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝗮𝗹 𝗿𝗲𝘃𝗶𝗲𝘄, 𝘁𝗵𝗲𝗿𝗺𝗼𝗱𝘆𝗻𝗮𝗺𝗶𝗰 𝘀𝘆𝘀𝘁𝗲𝗺 𝗺𝗼𝗱𝗲𝗹𝗶𝗻𝗴, and 𝗺𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝗮𝗹 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗻𝗼𝘃𝗲𝗹 𝘀𝗰𝗶𝗲𝗻𝘁𝗶𝗳𝗶𝗰 𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝘀. I assist researchers in 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗻𝗴, 𝗦𝘁𝗿𝗲𝘀𝘀-𝗧𝗲𝘀𝘁𝗶𝗻𝗴, and 𝗥𝗲𝗳𝗶𝗻𝗶𝗻𝗴 𝗘𝗺𝗲𝗿𝗴𝗶𝗻𝗴 𝗜𝗱𝗲𝗮𝘀—including 𝗔𝗜-𝗮𝘀𝘀𝗶𝘀𝘁𝗲𝗱 𝗮𝗻𝗱 𝗲𝗺𝗲𝗿𝗴𝗶𝗻𝗴 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝘀—by identifying logical gaps, assessing internal consistency, developing formal definitions, and translating conceptual frameworks into rigorous mathematical architectures. My work spans 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗖𝗼𝗻𝘀𝘂𝗹𝘁𝗶𝗻𝗴, 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝗳𝗶𝗰 𝗦𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻, 𝗝𝗼𝘂𝗿𝗻𝗮𝗹 𝗠𝗮𝗻𝘂𝘀𝗰𝗿𝗶𝗽𝘁 𝗥𝗲𝘃𝗶𝗲𝘄, 𝗧𝗵𝗲𝗼𝗿𝗲𝗺 𝗩𝗲𝗿𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻, 𝗣𝗿𝗼𝗼𝗳 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻, 𝗧𝗵𝗲𝗿𝗺𝗼𝗱𝘆𝗻𝗮𝗺𝗶𝗰 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴, 𝗖𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗣𝗵𝘆𝘀𝗶𝗰𝘀, 𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝗮𝗹 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁, and 𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝗮𝗹 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 for advanced scientific and engineering research. Recent collaborations include long-term consulting engagements in mathematical modeling, thermodynamic analysis, referee-level manuscript review, and the formalization of novel theoretical frameworks for publication-quality research. 𝗦𝗘𝗟𝗘𝗖𝗧𝗘𝗗 𝗥𝗘𝗖𝗘𝗡𝗧 𝗣𝗥𝗢𝗝𝗘𝗖𝗧𝗦 𝗔𝗗𝗩𝗔𝗡𝗖𝗘𝗗 𝗠𝗔𝗡𝗨𝗦𝗖𝗥𝗜𝗣𝗧 𝗥𝗘𝗙𝗜𝗡𝗘𝗠𝗘𝗡𝗧 & 𝗣𝗥𝗢𝗢𝗙 𝗩𝗔𝗟𝗜𝗗𝗔𝗧𝗜𝗢𝗡 (𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗲𝗱) Conducted a 128-hour research consulting engagement supporting an advanced theoretical physics manuscript through proof verification, derivation auditing, referee-risk assessment, logical consistency analysis, and journal-ready LaTeX preparation. 𝗧𝗛𝗘𝗥𝗠𝗢𝗗𝗬𝗡𝗔𝗠𝗜𝗖 𝗦𝗬𝗦𝗧𝗘𝗠 𝗠𝗢𝗗𝗘𝗟𝗜𝗡𝗚 (𝗢𝗻𝗴𝗼𝗶𝗻𝗴) Developing nonlinear thermal-energy balance models with analytical investigation and numerical validation. 𝗥𝗘𝗦𝗘𝗔𝗥𝗖𝗛 𝗠𝗔𝗡𝗨𝗦𝗖𝗥𝗜𝗣𝗧 𝗥𝗘𝗩𝗜𝗘𝗪 & 𝗧𝗘𝗖𝗛𝗡𝗜𝗖𝗔𝗟 𝗔𝗨𝗗𝗜𝗧 (𝗢𝗻𝗴𝗼𝗶𝗻𝗴) Reviewing advanced mathematics and physics manuscripts for derivation verification, notation consistency, and technical rigor. 𝗠𝗔𝗧𝗛𝗘𝗠𝗔𝗧𝗜𝗖𝗔𝗟 𝗙𝗥𝗔𝗠𝗘𝗪𝗢𝗥𝗞 𝗗𝗘𝗩𝗘𝗟𝗢𝗣𝗠𝗘𝗡𝗧 (𝗢𝗻𝗴𝗼𝗶𝗻𝗴) Evaluating and formalizing novel theoretical concepts, including AI-assisted research ideas, into mathematically defensible frameworks. 𝗦𝗘𝗥𝗩𝗜𝗖𝗘𝗦 ✓ Mathematical Modeling ✓ Thermodynamic & Physical System Modeling ✓ Differential Equations (ODEs, PDEs, Dynamical Systems) ✓ Scientific Computing & Numerical Methods ✓ Research Manuscript Review & Validation ✓ Mathematical Proof Verification ✓ Scientific Programming (Python, MATLAB, Maple, Mathematica, Fortran) ✓ CFD, Heat Transfer & Transport Phenomena ✓ LaTeX, Overleaf & Publication Support ✓ Journal, Thesis & Technical Report Preparation 𝗦𝗢𝗙𝗧𝗪𝗔𝗥𝗘 • Python • MATLAB • Maple • Mathematica • Fortran • COMSOL Multiphysics • ANSYS Fluent • LaTeX • Overleaf 𝗛𝗢𝗪 𝗜 𝗪𝗢𝗥𝗞 Every project begins with a focused milestone—such as a model review, derivation audit, framework evaluation, manuscript assessment, or computational validation—to establish a clear technical roadmap before expanding into larger engagements. If you need support with mathematical modeling, scientific computing, theoretical framework development, thermodynamic analysis, research manuscript review, or publication preparation, feel free to contact me. 𝗗𝗿. 𝗗𝘂𝗿𝗴𝗲𝘀𝗵 𝗞𝘂𝘀𝗵𝗮𝘄𝗮𝗵𝗮 𝗣𝗵𝗗 𝗔𝗽𝗽𝗹𝗶𝗲𝗱 𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝘀

⭐️ 𝑻𝒐𝒑 𝑹𝒂𝒕𝒆𝒅 - 𝑻𝒐𝒑 3% 𝒐𝒇 𝑻𝒂𝒍𝒆𝒏𝒕 𝒐𝒏 𝑼𝒑𝒘𝒐𝒓𝒌 ⭐️ I am a PhD Applied Mathematician, University Lecturer, and Research Consultant with 9+ years of experience in academic research, scientific writing, manuscript editing, and journal publication support. I have authored over 30 international research publications and helped researchers, graduate students, and professionals successfully complete and publish their work in Scopus- and Web of Science-indexed journals. I understand the challenges researchers face when preparing high-quality academic work under strict deadlines. My goal is to provide reliable, accurate, and professional support that helps clients achieve their academic and research objectives. Whether you need assistance with a research paper, thesis, dissertation, journal article, reviewer response, or publication process, I am committed to delivering work that meets the highest academic standards. In addition to academic writing and editing, I specialize in MATLAB programming, mathematical modeling, CFD simulations, Artificial Neural Networks (ANN), machine learning, and engineering research. My combined expertise in research and technical computing allows me to support both academic and engineering projects effectively. 🥇𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝗜 𝗢𝗳𝗳𝗲𝗿🥇 ✔ Research Paper Writing, Editing & Proofreading ✔ Thesis & Dissertation Support ✔ Q1/Q2 Journal Publication ✔ Journal Publication Assistance ✔ Model Development ✔ Reviewer Comments & Revision Responses ✔ Literature Reviews & Systematic Reviews ✔ Research Proposals & Technical Reports ✔ Academic Editing & Proofreading ✔ APA, MLA, Harvard & Chicago Formatting ✔ MATLAB Programming & Numerical Simulations ✔ Artificial Neural Networks (ANN) & Machine Learning ✔ Mathematical Modeling & Data Analysis ✔ Engineering & Scientific Research Support ✔ Case Study (Research, Editing and Proofreading) 🥇Why Work With Me?🥇 ✔ PhD Applied Mathematician ✔ 30+ International Research Publications ✔ 9+ Years of Research Experience ✔ Fast Communication and On-Time Delivery ✔ High-Quality Academic and Technical Work ✔ Publication Support for Scopus & Web of Science Journals Your success is my priority. Let's work together to transform your ideas into high-quality research and successful publications. #Publication #AcademicWriter #EditingandProofreading #ResearchWriter #ResearchPaper #Editor #APAFormatting #DissertationWriting #ThesisWriting #EditingandFormatting #Proofreading #EssayWriting #AcademicWriting #ResearchProposals #LiteratureReviews

I'm a Ph.D. in Bioinformatics specialized in scRNA-seq, metabarcoding, metagenomics, population genetics, biostatistics, structural bioinformatics, and phylogenetics. I hold a master's and bachelor's degree in Biotechnology with an emphasis in Bioinformatics, Molecular Biology, and Genetic Engineering. As a gold medal winner (Best Hardware category) of iGem 2022 with several published research papers and peer review experience for international journals, I offer expert assistance in: Core Bioinformatics & Research: • Experimental design and analysis • Research paper review and writing • Plasmid design and cloning strategies • NGS data analysis (RNA-seq, scRNA-seq, metagenomic) • Population genetics studies • Protein structure analysis • Phylogenetic analysis • Statistical analysis of biological data • Academic mentoring and supervision Biological Data Science Expertise: • Machine learning applications in biology (supervised/unsupervised learning) • Predictive modeling for biological systems • Multi-omics data integration and analysis • Big data handling and cloud computing for genomics • Database design and management for biological datasets • Data visualization and interactive dashboards for biological insights • Algorithm development for biological pattern recognition • Automated analysis pipelines and workflow optimization With over 50 successful projects delivered to international biotechnology companies and research labs with top-tier feedback, I bridge the gap between complex biological data and actionable scientific insights. Whether you are a startup needing a robust NGS pipeline or a research group looking for high-level data interpretation and scientific writing, I provide the expertise of a published scientist with the agility of a senior freelancer.

I help organizations turn complex data into accurate forecasts, predictive models, and actionable insights using machine learning, statistics, and applied mathematics. I currently work as a Research Scientist at the University of Michigan and hold a dual PhD in Mechanical Engineering and Computational Mathematics. My expertise includes time-series forecasting, statistical modeling, machine learning, predictive analytics, signal processing, uncertainty quantification, and decision-support systems. I specialize in challenging datasets where noise, missing information, uncertainty, or complex system behavior make standard approaches unreliable. What I can help you with: • Time-series forecasting and predictive analytics • Machine learning model development and evaluation • Statistical analysis and uncertainty quantification • Predictive modeling for business, research, and engineering decisions • Classification on difficult or noisy datasets • Feature engineering, data preprocessing, and model validation • Model debugging and performance improvement • End-to-end ML pipelines in Python • Signal processing and biomedical data analysis • Simulation, surrogate modeling, and optimization workflows • Decision-support models for real-world systems Experience Highlights: • Developed machine-learning models for biomedical signal classification that improved accuracy by 15% over conventional feature-engineering approaches. • Developed custom statistical and machine-learning algorithms for identifying patterns, data drift, and behavioral changes in noisy, uncertain, and stochastic datasets. • Built predictive models and surrogate modeling systems that replaced computationally expensive simulations, enabling rapid design evaluation and optimization. • Conducted research in forecasting, stochastic systems, machine learning, and scientific computing, resulting in peer-reviewed publications, open-source software contributions, and conference presentations. Tools & Technologies: Python, Pandas, NumPy, SciPy, scikit-learn, XGBoost, TensorFlow, PyTorch, SQL, Jupyter, Matplotlib, Statistical Modeling, Machine Learning, Time-Series Forecasting, Predictive Modeling, Signal Processing, Data Analysis, Feature Engineering, Model Validation, Optimization, Scientific Computing. My Approach: Most machine-learning problems do not fail because of the model itself - they fail because the data is noisy, incomplete, poorly structured, or difficult to interpret. My focus is on building reliable models, validating assumptions, reducing overfitting, and delivering results that are useful for real-world decisions. If you're working on forecasting, predictive modeling, machine learning, statistical analysis, model validation, or complex data challenges, I’d be happy to discuss how I can help.

I help genomics companies, academic research labs, and PhD researchers turn complex sequencing and clinical datasets into publication-ready results, grant-winning insights, and actionable biological discoveries. With hands-on expertise in bulk RNA-Seq, single-cell RNA-Seq, multi-omics integration, and clinical biostatistics, I deliver more than analysis; I provide scientific interpretation, reproducible pipelines, and clear visualisations that accelerate decision-making. Whether you're: Identifying novel therapeutic targets Dissecting cellular heterogeneity Integrating transcriptomics with epigenomics Validating biomarkers for clinical studies Preparing figures for high-impact journals I ensure your data becomes a defensible scientific asset — not just processed output. Let's transform your raw data into meaningful biological insight. 🧬 Core Services 1️⃣ Bulk RNA-Seq & Transcriptome Analysis Tools: HISAT2, STAR, DESeq2, edgeR Deliverables: Differential expression analysis Pathway & enrichment analysis Publication-ready plots Reproducible pipelines Best For: Mechanistic studies, biomarker discovery, therapeutic target identification. 2️⃣ Single-Cell RNA-Seq (scRNA-Seq) Tools: Cell Ranger, Seurat, Monocle Deliverables: Clustering & annotation Trajectory analysis Rare cell population detection Integration of multiple datasets Best For: Tumour microenvironment, immune profiling, tissue heterogeneity. 3️⃣ Multi-Omics Data Integration Transcriptomics + Epigenomics RNA-Seq + Clinical Metadata Cross-platform data harmonisation Outcome: Systems-level biological insight and stronger mechanistic conclusions. 4️⃣ Clinical Biostatistics & Modelling Logistic regression Survival analysis Bayesian models ML classifiers (Random Forest, XGBoost, LASSO) Clinical dataset interpretation Outcome: Robust statistical validation for publications, diagnostics, and trials. 🧪 Technical Expertise Programming: Python, R, Bash, SQL Bioinformatics: GATK, STAR, DESeq2, Seurat, QIIME, MACS2 Statistics & ML: Regression, Bayesian modelling, AI/ML pipelines Visualization: ggplot2, Matplotlib Infrastructure: HPC environments, reproducible workflows, Git 🎯 Stronger Call to Action If you need reliable bioinformatic support for your lab, startup, or thesis, let's discuss your dataset and research goals. Prioritise clarity, reproducibility, and scientific rigour.

Your simulation is too slow, too expensive, or breaking down at the boundaries. I build machine learning surrogates and custom PINNs in PyTorch that work where standard solvers fail. I am a PhD computational researcher with a 100% Job Success Score. My last PINN project delivered a fully validated elastoplasticity framework, on time, 5-star review. Before that, I built a PINN-based equation discovery system for turbulent Navier-Stokes at Re=10,000 using sparse regression. These are not portfolio pieces. They are production deliverables. If you hire me, you are not getting a coder who follows instructions. You are getting someone who will tell you when your approach is wrong and what the right one is. -------------------------------------------------------------- RECENTLY DELIVERED -------------------------------------------------------------- - A five-figure number theory project spanning several months: 7 custom programs for Diophantine constraint analysis, spectral tools, and a standalone desktop application. - 200+ Chain-of-Thought reasoning traces for AI training in Olympiad-level algebra, geometry, probability, and abstract algebra. -------------------------------------------------------------- WHAT I BUILD FOR YOU -------------------------------------------------------------- - Custom PINNs in PyTorch for forward, inverse, and multi-physics problems - High-fidelity surrogate models that replace expensive FEM or CFD simulations - PINN-based equation discovery using sparse regression (STRidge) for data-driven physics - Debugging and mathematically correcting existing scientific ML architectures that are failing -------------------------------------------------------------- AI TRAINING DATA & MATHEMATICAL REASONING -------------------------------------------------------------- - Chain-of-Thought reasoning traces for AI fine-tuning in advanced and Olympiad-level mathematics - Rigorous, error-free datasets covering Geometry, Probability, Algebra, and Abstract Algebra - Custom algorithmic solvers and computational engines for specialized mathematical problems -------------------------------------------------------------- CREDENTIALS THAT MATTER HERE -------------------------------------------------------------- - 6-month research placement at Imperial College London in nonlinear wave equations and soliton dynamics - University instructor in Calculus and Numerical Analysis at GIKI, giving me the pedagogical depth to build AI math logic that is both rigorous and explainable - 200+ mathematical reasoning traces designed for AI training clients - Spectral analytics tools built for Diophantine constraints and complex signal synthesis -------------------------------------------------------------- TECH STACK & CORE COMPETENCIES -------------------------------------------------------------- Languages: Python, PyTorch, DeepXDE, TensorFlow, NumPy, SciPy AI & ML: PINNs, STRidge, Deep Learning, RLHF, Chain-of-Thought Math Logic Domains: Nonlinear PDEs, Inverse Problems, Turbulent Flows, Soliton Dynamics, Elastoplasticity, Numerical Analysis, Olympiad Mathematics -------------------------------------------------------------- Describe your problem in a message. I will tell you in plain terms whether I can solve it and exactly how. -------------------------------------------------------------- KEYWORDS -------------------------------------------------------------- Scientific Machine Learning | Physics-Informed Neural Networks | PINN | Applied Mathematics | Artificial Intelligence | Deep Learning | PyTorch | Partial Differential Equations | PDE Solver | Computational Science | Scientific Computing | AI Data Generation | RLHF | Chain of Thought | CoT | LLM Fine-Tuning | Large Language Models | Synthetic Data Generation | Supervised Fine-Tuning | SFT | Generative AI Data | Prompt Engineering | AI Alignment | RAG | Subject Matter Expert | SME | Mathematical Reasoning | Numerical Methods | Algorithm Development | Mathematical Modeling | Machine Learning Engineer | Data Scientist | AI Tutor | Math Logic | DeepXDE | TensorFlow | JAX | Neural Operators | Fourier Neural Operator | FNO | DeepONet | Solitons | Solid Mechanics | Elastoplasticity | Multiphysics | Ordinary Differential Equations | ODE | Optimization | Inverse Problems | Spectral Methods | Abstract Algebra | Calculus | Geometry | Topology | Probability | Linear Algebra | Discrete Mathematics | Stochastic Processes | High-Performance Computing | HPC | GPU Optimization | CUDA | C++ | Python Developer | NumPy | SciPy | Pandas | Matplotlib | Data-Driven Discovery | R&D | LaTeX | Technical Writing | Research Scientist